Identify Prognostic Biomarkers of Lung Cancer

August 14, 2021 updated by: RenJi Hospital

Multi-omics Combined With Clinical Data Analysis to Identify Prognostic Biomarkers of Lung Cancer

Multi-omics and Clinical Data Analysis is potential to predict the prognosis of lung cancer patients.

Study Overview

Status

Recruiting

Conditions

Detailed Description

Lung cancer is the leading cause of cancer-related death in China. In order to improve prognosis of lung cancer as well as provide new therapeutic targets, the identification of effective biomarkers for the prognosis of lung cancer is of great significance. It has been reported that some small molecules such as lncRNA, circRNA and polypeptides in human plasm have good prospects in diagnosing or evaluating the stage of diseases. In this study, we planned to use multi-omics combined with clinical data to discovery some small molecules that are potential to predict the prognosis of lung cancer patients. In addition, we want to construct a new risk score model that provide a candidate model for prognostic evaluation of lung cancer. And we hope our study can provide insights for precision immunotherapy of lung cancer by exploring the differences in clinical characteristics, tumor mutation burden, and tumor immune cell infiltration between different risk score groups.

Study Type

Observational

Enrollment (Anticipated)

500

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • China
      • Shanghai, China, 021
        • Recruiting
        • Renji Hospital, Shanghai Jiaotong University School of Medicine

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 80 years (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Individuals aged between 18 and 80 years old. Patients with diagnosis of lung cancer or healthy controls without any history of tumor will be eligible for our enrollment.

Description

Inclusion Criteria:

  • Patients diagnosed with lung cancer;
  • Untreated lung cancer patients;
  • No history of chronic or serious diseases, such as cardiovascular disease, liver disease, kidney disease, respiratory disease, blood disease, lymphatic disease, endocrine disease, immune disease, mental disease, neuromuscular disease, gastrointestinal system disease, etc.

Exclusion Criteria:

  • Patients with other tumors;
  • Lung cancer patients who had been treated;
  • Abnormal liver and kidney function;
  • Acute and chronic infectious diseases

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
healthy control
healthy people
lung cancer
patients diagnosed with lung cancer

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Identify some prognostic biomarkers in lung cancer.
Time Frame: 1 week
  1. Our study will identify some biomarkers that can predict the prognosis of lung cancer patients.
  2. Our study will construct a new risk score model that provide a candidate model for prognostic evaluation of lung cancer.
  3. Our research will provide insights for precision immunotherapy of lung cancer by exploring the differences in clinical characteristics, tumor mutation burden, and tumor immune cell infiltration between different risk score groups.
1 week

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

RenJi Hospital

Investigators

  • Principal Investigator: Huijing Huang, RenJi Hospital

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

July 1, 2020

Primary Completion (Anticipated)

September 20, 2021

Study Completion (Anticipated)

September 30, 2021

Study Registration Dates

First Submitted

July 27, 2021

First Submitted That Met QC Criteria

August 14, 2021

First Posted (Actual)

August 18, 2021

Study Record Updates

Last Update Posted (Actual)

August 18, 2021

Last Update Submitted That Met QC Criteria

August 14, 2021

Last Verified

August 1, 2021

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • MKM2021-720

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

There is no plan to make individual participant data (IPD) available to other researchers.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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